ReclinerJS – Local CouchDB inside your Browser

Hacker News

Introducing Recliner-JS: a CouchDB-like database that runs directly in your browser! Get ready to experience the power of a seamless document and attachment management system, just like CouchDB, but with the added convenience of being accessible through a familiar REST API. Imagine effortlessly retrieving your docs and attachments with a simple URL: <img src=`/recliner/dbname/doc_id/attachment_name`> But that's not all! This library takes things to the next level with its cutting-edge partial content streaming capabilities. Lazy Cloud Attachments ensure that your browser only downloads the attachments you need, when you need them, optimizing performance and efficiency. Built from the ground up using pure, vanilla JavaScript, this library is a testament to my commitment to simplicity and robustness. Don't just take my word for it – head over to the GitHub repo and explore the usage examples and working demos for yourself! Get ready to revolutionize your web development experience.

Visit product View on Hacker NewsMar 9, 2024

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos

76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

62%62% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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